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Found 10 papers, 4 papers with code
A Survey of Detection Methods for Die Attachment and Wire Bonding Defects in Integrated Circuit Manufacturing
Defect detection plays a vital role in the manufacturing process of integrated circuits (ICs).
Probabilistic Neural Network to Quantify Uncertainty of Wind Power Estimation
The developed network captures both model and noise uncertainty which is found to be useful tools in assessing performance.
Multitasking Deep Learning Model for Detection of Five Stages of Diabetic Retinopathy
The regression model learns the inter-dependency between the stages and outputs a score corresponding to the severity level of DR generating a higher score for a higher severity level.
Deep Learning-Based Human Pose Estimation: A Survey
Furthermore, 2D and 3D human pose estimation datasets and evaluation metrics are included.
Vision and Inertial Sensing Fusion for Human Action Recognition : A Review
Human action recognition is used in many applications such as video surveillance, human computer interaction, assistive living, and gaming.
Personalization of Hearing Aid Compression by Human-In-Loop Deep Reinforcement Learning
Existing prescriptive compression strategies used in hearing aid fitting are designed based on gain averages from a group of users which are not necessarily optimal for a specific user.
Automatic exposure selection and fusion for high-dynamic-range photography via smartphones
In this paper, a method for automatically selecting the exposure settings of such images is introduced based on the camera characteristic function.
Image Segmentation Using Deep Learning: A Survey
Image segmentation is a key topic in image processing and computer vision with applications such as scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, among many others.
Guidelines and Benchmarks for Deployment of Deep Learning Models on Smartphones as Real-Time Apps
From the variety of available deep learning tools, the most suited ones are used in this paper to enable real-time deployment of deep learning inference networks on smartphones.
A Convolutional Neural Network Smartphone App for Real-Time Voice Activity Detection
This paper presents a smartphone app that performs real-time voice activity detection based on convolutional neural network.
