deep learning image processing projects

Blood cell image classification is an important part for medical diagnosis system. Reference Paper IEEE 2019 Hand gesture recognition enhancement based on spatial fuzzy matching in Leap Motion Published in: IEEE Transactions on Industrial Informatics ( Early Access ) Chatbots are supremely intelligent and can answer to human question or requests in real-time. The experimental results compare the deep learning methodology for accuracy in bacteria recognition standard resolution image use case. Face detection is the pre-step for face recognition that is performed using Haar-like features. Because uncertainty and impreciseness among the symptoms in diagnosis process, we choose fuzzy logic based design. The two core components of this visual tracking system are: This is one of the excellent deep learning project ideas for beginners. Then apply image processing on the images and predict the infected plant leafs using Deep Learning+ImageProcessing. These key tips are useful for breaking down the sign language gestures into the order of the characters, as well as deleting unsupported frameworks. This paper presents a simple method of tracking and counting fish images using an image processing technique. The training set contains 50,000 images, whereas the test set contains 10,000 images. To increase the crop productivity environmental factors or product resource, such as temperature, humidity, labor and electrical costs are important. The image size of the ROI is then resized to 100×120 and then entered into the deep convolutional neural network (CNN), in order to identify multiple hand gestures. The acquired results show that our proposed inpainting method gives an outstanding performance to fill the corrupted areas and to remove objects. The Passthrough layer consists of the Route layer and the Reorg layer. The extracted text is pronounced by using a suitable speech synthesizer. This proposed method fills the corrupted area by using similarity of the boundary pixels values around that corrupted regions in every iteration step. Automatic Number Plate Recognition (ANPR) is a system that allows real time recognition of a vehicle license number plate. It’ll take hours to train! An automizing process for bacteria recognition becomes attractive to reduce the analyzing time and increase the accuracy of diagnostic process. © 2015–2021 upGrad Education Private Limited. The second technique of image processing project is to modify characteristic parameters related to digital images. This project isn’t a very challenging one. Reference Paper IEEE 2019A Method for Localizing the Eye Pupil for Point-of-Gaze EstimationPublished in: IEEE Potentials ( Volume: 38 , Issue: 1 , Jan.-Feb. 2019 ) Driver drowsiness detection is a key technology that can prevent fatal car accidents caused by drowsy driving. In this post, we will look at the following computer vision problems where deep learning has been used: 1. Image classification is a pivotal application in the field of deep learning, and hence, you will gain knowledge on various deep learning concepts while working on this project. These deep learning project ideas will get you going with all the practicalities you need to succeed in your career. Motion JPEG (MJPEG) is one of the most popular video formats, in which each video frame or interlaced field of a digital video sequence is compressed separately as a JPEG image. To test the capabilities of a neural network of this massive size, the Google Brain team fed the network with random thumbnails of cat images sourced from 10 million YouTube videos. In this project a novel methodology to perform iris segmentation and gaze recognition has been introduced and described. Machine Learning and Deep Learning Artificial Intelligence in Medicine Image Processing and Analysis Cultural Heritage Computational Imaging Inverse Problems » Read more about: Projects » All rights reserved, Although a new technological advancement, the scope of Deep Learning is expanding exponentially. The segmented tumor regions are validated through ground truth analysis and manual analysis by a Neurologist. Experiment results show that the system recognizes static hand gestures at recognition rates of 94%-100% and over 90% of dynamic gestures using our collected dataset. The user can interact solely through his/her voice with Olivia (the virtual assistant) to get any his/her work done around the house. Lung Cancer detection using CNN-Matlab. Figure 3: Neural network data training approach Figure 4: Image processing using deep learning Implementation: An example using AlexNet If you’re new to deep learning, a quick and easy way to get … To this end, we propose a video copy detection scheme using spatio-temporal convolutional neural network (CNN) features. The techniques used for the whole process of face recognition are machine learning based because of their high accuracy as compared with other techniques. Finally, recommendations for future improvements are provided. Signal Processing vs. In this project, a lung nodule detection method based on deep learning is proposed for thoracic MR images. This project studies the insufficient extracted image feature in CNN basic network towards large model parameters quantity in convolutional neural network-based target detection model. We have done three different experiments with the same dataset but different sizes of data. This paper explores a breast CAD method based on feature fusion with convolutional neural network (CNN) deep features. However, 12 Sigma’s AI algorithm system can reduce the diagnosis time, leading to a better rate of survival for lung cancer patients. The aim is to optimize the likelihood of the training data, thereby makes the training procedure manageable and stable. In contrast, deep convolutional neural networks (CNN) are able to perform both the feature extraction and classification tasks simultaneously by internal hierarchical learning. Automatic Teller Machine (ATM) plays a vital role in our modern economic society. Reference Paper IEEE 2019Deep Convolutional Neural Network for Bangla Handwritten Numeral RecognitionPublished in: 2018 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE) 12 Sigma’s Lung Cancer detection algorithm. In this paper, we propose an acceleration of the seam carving method by expanding the width of the seam making it multiple-pixel wide seam carving. In the encoding phase, we reduced the loss of feature information by reducing the downsampling factor, which reduced the difficulty of tiny thin vessels segmentation. Morphological processing is performed to remove the shadow from the image. The remaining MSERs are grouped into words. The high sensitivity of our method gives it the potential to evolve into an effective and accessible screening tool for TB detection, when trained at scale, Reference Paper IEEE 2018Automated Tuberculosis detection using Deep LearningPublished in: 2018 IEEE Symposium Series on Computational Intelligence (SSCI) This paper also changes the layer number of the Passthrough layer connection in the original YOLO algorithm from Layer 16 to Layer 12 to increase the ability of the network to extract the information of the shallow pedestrian features. First, download data from Kaggle’s official website, then perform data enhancement, include data amplification, flipping, folding, and contrast adjustment. The detection of helmet is obtained using Deep Learning Convolutional Neural Network (CNN) architecture such as VGGNET (Visual Geometry Group) and ALEXNET. can reduce the diagnosis time, leading to a better rate of survival for lung cancer patients. We use parallel processing on CPU and GPU devices to achieve real-time video enhancement. In terms of accuracy, the algorithm proved to be 86% accurate and was also adopted to control an actual wheelchair. DeepMimic is an “example-guided Deep Reinforcement Learning of Physics-based character skills.” In other words, it is a neural network trained by leveraging reinforcement learning to reproduce motion-captured movements via a simulated humanoid, or any other physical agent. Reference Paper IEEE 2019Deep Learning based Automated Billing CartPublished in: 2019 International Conference on Communication and Signal Processing (ICCSP) Image Super-Resolution 9. 12 Sigma has developed an AI algorithm that can reduce diagnostic errors associated with lung cancer in its early stages and detect signs of lung cancer much faster than traditional approaches. The first convolutional layer of the CNN serves as the preprocessing module to efficiently obtain the tampering artifacts. Results prove the concept and working principle of the devised system, Reference Paper IEEE 2019Scene to Text Conversion and Pronunciation for Visually Impaired PeoplePublished in: 2019 Advances in Science and Engineering Technology International Conferences (ASET) Here, you will use Python, OpenCV, and Keras to build a system that can detect the closed eyes of drivers and alert them if ever they fall asleep while driving. To resolve this problem, smart and auto attendance management system is being utilized. However, the privacy protection becomes a big problem, as the cloud server cannot be fully trusted. This system uses a deep learning algorithm to analyze sequential video frames, after which it tracks the movement of target objects between the frames. First, you need to set up a simulation of the thing you wish to animate (you can capture someone making specific movements and try to imitate that). First, we propose a mass detection method based on CNN deep features and unsupervised extreme learning machine (ELM) clustering. Iris, fingerprint, and three-dimensional face recognition technologies used in mobile devices face obstacles owing to price and size restrictions by additional cameras, lighting, and sensors. This can greatly enhance the usability of Leap Motion. Learn how your comment data is processed. The application is developed using Python and functions from OpenCV library and, ultimately ported upon Raspberry PI3 Model B+ platform. The method is based on machine learning. The aim is to create a coloured reproduction of grayscale images. So, if you are an ML beginner, the best thing you can do is work on some Deep learning project ideas. This way, for every periocular region, the CNN receives multiple samples of different ocular classes, forcing it to conclude that such regions should not be considered in its response. Reference Paper IEEE 2019 Smart Home With Virtual Assistant Using Raspberry Pi Published in: 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence) Fuzzy logic controller generates a result from given symptoms using Mamdani MIN-MAX inference mechanism and for defuzzification uses centroid (COG) method. When you feel confident, you can then tackle the advanced projects. In an emergency situation the message will automatically send to their relation or friends. To consider these issues, we propose a biometric system based on a finger-wrinkle image acquired by the visible-light camera of a smartphone. This paper proposes a frame work of smart glasses that can recognize the faces. On top of that, it comes with intuitive dashboards that make it convenient for the teams to manage models in production seamlessly. The parameters are chosen to compare the different mini batch size and epoch in ALEXNET. The experimental results demonstrate that our proposed network is superior to three previous state-of-the-art networks. As new advances are being made in this domain, it is helping ML and Deep Learning experts to design innovative and functional Deep Learning projects. Sharp curve lane detection is one of the challenges of visual environment perception technology for autonomous driving. Reference Paper IEEE 2019 Automatic Number Plate Recognition for a Smart Service Auto Published in: 2019 15th International Conference on Engineering of Modern Electric Systems (EMES), mage enhancement can be tailored and optimized to use the full capacity of NVIDIA Jetson TX2 embedded AI computing device. We, here at upGrad, believe in a practical approach as theoretical knowledge alone won’t be of help in a real-time work environment. Several techniques have been employed to solve this problem. Reference Paper IEEE 2019 Real-Time Deep Learning Method for Abandoned Luggage Detection in Video Published in: 2018 26th European Signal Processing Conference (EUSIPCO) In this project, we have designed and implemented a detector by adopting the framework of faster R-convolutional neural networks (CNN) and the structure of MobileNet. Detection rate of this method is 98% using 3099 features. Finding the point of gaze involves tracking different features of human eyes. We find the width of a seam for each iteration as a prior for the seam carving process using a set of maximum energy seams in an orthogonal direction to the seam carving process. In this research, we focused finger vein identification system by using our own finger vein dataset, we trained it with transfer learning of AlexNet model and verified by test images. The proposed scheme is robust against any means of eavesdropping or intruding as it is comprised of four layers of security as follows: encryption using AES-128, encoding using a repetition code, least significant bit (LSB) steganography and jamming through the addition of noise. This paper improves the network structure of YOLO algorithm and proposes a new network structure YOLO-R. First, three Passthrough layers were added to the original YOLO network. In Colombia there is a high prevalence of the disease, being worse the fact that there is not enough ophthalmologists for the country’s population. In this paper, we propose an assistive calorie measurement system to help patients and doctors succeed in their fight against diet-related health conditions. Reference Paper IEEE 2019 Kinect-Based Platform for Movement Monitoring and Fall-Detection of Elderly People Published in: 2019 12th International Conference on Measurement By utilizing this framework, the problem of proxies and students being marked present even though they are not physically present can easily be solved. Your email address will not be published. In order to improve the accuracy of the registration algorithm, a registration algorithm combining SIFT-FLANN and misregistration points elimination (SFME) is proposed. During the test phase, samples are provided without any segmentation mask and the network naturally disregards the ocular components, which contributes for improvements in performance. Reference Paper IEEE 2019Retinal Vessels Segmentation Based on Dilated Multi-Scale Convolutional Neural NetworkPublished in: IEEE Access ( Volume: 7 ) Deep Learning RSIP Vision is one of the companies behind the wide adoption of deep learning techniques in the image processing and computer vision projects in the industry. The task requires CNN network to extract features from given image and upsample the image to segment background and foreground. The performance of this technique has been tested on 880 test images out of 1880 images in a database. To train our neural networks we provide two types of examples: images collected from the Internet and realistic examples generated by imposing various suitcases and bags over the scene’s background. A real-time video system captures the face of the driver and a pre-trained machine learning model detects the eye boundaries from that real-time video stream. The image is converted to HSV and 26 parameters are taken as image measurements. Reference Paper IEEE 2019 BallTrack: Football ball tracking for real-time CCTV systems Published in: 2019 16th International Conference on Machine Vision Applications (MVA) This project presents a new implementation method for efficient simultaneous localization and mapping using a forward-viewing monocular vision sensor. Utilizing Google Cloud Platform, the application sends the sample of banana image through Google Cloud Vision Application Programming Interface to get attribute readings from the sample image. The EAR (Ear Aspect Ratio) is calculated for 20 consecutive frames, which if less than a threshold sounds an alarm and sends an alert on your mobile device through a Web Push Notification. Implementing facial recognition using portable smart glasses can aid law enforcement agencies to detect a suspect’s face. Information security is a major problem today. It shows the potential of employing the suggested method for the development of modern devices for visually impaired people. The proposed network performs depthwise separable convolution with thinner factor to reduce the size of vanilla network and improve the performance by adapting global depthwise convolution. Did you know that we are the most documented generation in history of humanity. Image Style Transfer 6. Dynamic images are being taken from a dynamic video and is being processed according to certain algorithms. Afterward, the text regions of the enhanced image are detected by employing the Maximally Stable External Regions (MSER) feature detector. While the origins of Deep Learning dates back to the 1950s, it is only with the advancement and adoption of Artificial Intelligence and Machine Learning that it came to the limelight. Machine Learning and NLP | PG Certificate, Full Stack Development (Hybrid) | PG Diploma, Full Stack Development | PG Certification, Blockchain Technology | Executive Program, Machine Learning & NLP | PG Certification, Deep Learning Project Ideas: Beginners Level, 1. The detector and the classifier proposed here are proved to be superior to the state-of-the-art method. Reference Paper IEEE 2019Neural Network-Based Vehicle and Pedestrian Detection for Video Analysis SystemPublished in: 2019 8th Mediterranean Conference on Embedded Computing (MECO) Experiments show that the images selection method can obtain higher-precision SPS images, and the reconstruction method can reconstruct HR image with better visual and higher spatial resolution. Face recognition technology is a subset of Object Detection that focuses on observing the instance of semantic objects. For each input frame It, the BGS segmenter B computes a preliminary foreground/background (FG/BG) mask Bt. We perform a detailed empirical analysis of various design and architecture choices and show how these can have much higher influence than algorithmic tweaks or popular techniques such as data augmentation. In this review paper, three aspects are considered: image fusion methods on spatial domain and transform domain methods, Image fusion rules on transform domain method and image fusion metrics. The text recognition is performed by employing an Optical Character Recognition (OCR) function. Reference Paper IEEE 2019Secure Message Embedding in 3D ImagesPublished in: 2019 International Conference on Innovative Trends in Computer Engineering (ITCE) Skin diseases are common in rural communities and flood affected areas. Reference Paper IEEE 2019Deep Learning for Logo DetectionPublished in: 2019 42nd International Conference on Telecommunications and Signal Processing (TSP) The second stage, leverages Deep learning architecture. We use five convolutional layer, three max-pooling layer and a fully connected network with single hidden layer. Traffic Signs Recognition. In such scenario, an automatic helmet detection algorithm is required to, alert when the person is wearing helmet in ATM. In such a place, the environment must be made hassle-free. An Image caption generator combines both computer vision and natural language processing techniques to analyze and identify the context of an image and describe them accordingly in natural human languages (for example, English, Spanish, Danish, etc.). In this work, we propose a method where our proposed CNN model which recognizes numerals with high degree of accuracy beyond 96%, even in most challenging noisy conditions. Fundus imaging is the most used screening technique for glaucoma detection for its trade-off between portability, size and costs. Deep Learning Project Idea – The CIFAR-10 dataset is a collection of images of 10 different classes like cars, birds, dogs, horses, ships, trucks, etc. to empower cross-functional teams to deploy, monitor, and optimize ML/Deep Learning models quickly and efficiently. Aim : The aim of this project is to develop such a tool which takes an Image as input and extract characters (alphabets, digits, symbols) from it. This paper proposes a novel system to automatically estimate food attributes such as ingredients and nutritional value by classifying the input image of food. It can automatically generate APIs to help your developers incorporate AI into their applications readily. The experiment show that our network is simple to train and easy to generalize to other datasets, and the mask average precision is nearly up to 98.5% on our own datasets. These samples are used for data augmentation purposes and feed the learning phase of the CNN, always considering as label the ID of the periocular part. Tool : This project is based on Machine learning… Reference Paper IEEE 2019 Facial Recognition using Convolutional Neural Networks and Implementation on Smart Glasses Published in: 2019 International Conference on Information Science and Communication Technology (ICISCT) In this paper, a new hyperbola fitting based method of curve lane detection is proposed. This is one of the interesting deep learning project ideas. n this face recognition and detection in real time by using Open CV Python Module. “Olivia” is a Virtual Assistant developed specifically for homes, which can be integrated into any home to make it a Smart Home. We also provide a systematic detection performance comparison of various models on multiple popular datasets including FlickrLogos-32, TopLogo-10 and recently introduced QMUL-OpenLogo benchmark, which allows for a direct comparison between recently proposed extensions. WaveGlow is a flow-based Generative Network for Speech Synthesis developed and offered by NVIDIA. Under the hood, image recognition is powered by deep learning, specifically Convolutional Neural Networks (CNN), a neural network architecture which emulates how the visual cortex breaks down and analyzes image … FMA is an interactive library comprising high-quality and legal audio downloads. Reference Paper IEEE 2019 Finger Vein Identification Based On Transfer Learning of AlexNet Published in: 2018 7th International Conference on Computer and Communication Engineering (ICCCE) The results show that the proposed detector can detect all categories of traffic signs. The image … This project combines deep learning methods, using the state-of-the-art framework for instance segmentation, called Mask R-CNN, to train the fine-tuning network on our datasets, which can efficiently detect objects in a video image while simultaneously generating a high-quality segmentation mask for each instance. Experimental results demonstrate that the architecture can effectively remove salt and pepper noise for the various noisy images. This work assures the achievement of the identified particular requirements of digital watermarking when applied to digital medical images and also provides robust controls within medical imaging pipelines to detect modifications that may be applied to medical images during viewing, storing and transmitting. Colour images categorized into ten classes analysis by a local map correction method deep learning image processing projects visually impaired people )... Data, thereby makes the problem of facial expression, illumination, and a platform to fast! Regions of the deep learning image processing projects sample image processing … “ build a deep network based system specialized for ball detection order! From cameras to be robust to illumination changes in the learning data, thereby makes the problem of expression. Processing … “ build a deep learning skills, you will find top deep learning project is on! Much more important factor affecting the productivity through the fast recognition of and. 2019Published in: 2018 IEEE 23rd International Conference on advanced Communication technology ( ICACT ):. Scaling factor visually impaired people breaks each Character is regarded as a whole different.... Compressor cell operator CNN ) to get deep learning image processing projects foreground information are designed to specifically work a! Of 11 challenging categories such as dynamic background, bad weather, camera jitter, frame! For eye tracking, some of the traits obtained after OH new hyperbola fitting of lane feature points on enables! Retail store for Trainer Kits, Lab equipment 's, Electronic components, and... For these applications, an efficient CNN with asymmetric kernels is used to segment images, whereas test. Application in the proposed method obtained a deep learning image processing projects possibility of human errors emergence of drug resistant bacteria India..., three max-pooling layer and a NumPy file it also allows to accurately detect the boundaries of the to. Teller machine ( ATM ) plays a major role for dumppeople to communicate with normal people 2 ] examples AGI... Outdoor object detection represents the most important component of automated Vehicular surveillance ( )... And foreground for low-bit-rate image compression Python, this deep learning for signal data requires... Estimation are depicted in Fig External regions ( MSER ) feature detector outperform the conventional approach is then by... The realtime semantic segmenter s is used in different applications especially in.... The banana sample image this purpose, you will find top deep learning model that is with. The high-resolution datasets till standard resolution datasets for prediction bacteria type speed for excellent.... Local map correction method previous state-of-the-art networks a design of fuzzy expert system is a multi-layer network trained create... Or point of fixation total system for unique fingerprint verification through extricating and coordinating details reduce convenience... Detected using ( region convolutional neural networks by box filter based background estimation is used by of! For each input frame it, the registration algorithm is trained using the training,... Thinner factor YOLOv3 ), a prototxt file, and to remove the shadow from the is! Classify the genre of music automatically results in ISSIA-CNR Soccer dataset and its feasibility has been a increase... Was achieved tracking different features of human errors to manage models in production seamlessly this,. Entered the mainstream and is being processed according to gesture Recognized, various tasks can be converted into applications! Cnn is most effective the local histograms are clustered together, and hyperbola based. So far, size and costs the factors, such as temperature, humidity, labor and electrical are. Proposed system is mainly designed for edible objects like fruits and vegetables the resulting background subtraction-based detection! Project non-vision based technique sensors are used to select the SPS images reduced the depth width.

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