A comprehensive review of object detection with deep learning
R Kaur, S Singh - Digital Signal Processing, 2023 - Elsevier
In the realm of computer vision, Deep Convolutional Neural Networks (DCNNs) have
demonstrated excellent performance. Video Processing, Object Detection, Image …
demonstrated excellent performance. Video Processing, Object Detection, Image …
A comprehensive and systematic look up into deep learning based object detection techniques: A review
Object detection can be regarded as one of the most fundamental and challenging visual
recognition task in computer vision and it has received great attention over the past few …
recognition task in computer vision and it has received great attention over the past few …
A survey of deep learning-based object detection
Object detection is one of the most important and challenging branches of computer vision,
which has been widely applied in people's life, such as monitoring security, autonomous …
which has been widely applied in people's life, such as monitoring security, autonomous …
Object detection using deep learning methods in traffic scenarios
A Boukerche, Z Hou - ACM Computing Surveys (CSUR), 2021 - dl.acm.org
The recent boom of autonomous driving nowadays has made object detection in traffic
scenes a hot topic of research. Designed to classify and locate instances in the image, this is …
scenes a hot topic of research. Designed to classify and locate instances in the image, this is …
A survey on deep learning approaches to medical images and a systematic look up into real-time object detection
The article focuses on the gentle introduction of Artificial Intelligence and the concepts of
machine learning (ML) and deep learning (DL). The rapid developments made in DL …
machine learning (ML) and deep learning (DL). The rapid developments made in DL …
Application of deep learning convolutional neural networks for internal tablet defect detection: high accuracy, throughput, and adaptability
Tablet defects encountered during the manufacturing of oral formulations can result in
quality concerns, timeline delays, and elevated financial costs. Internal tablet cracking is not …
quality concerns, timeline delays, and elevated financial costs. Internal tablet cracking is not …
BNAS: Efficient neural architecture search using broad scalable architecture
Efficient neural architecture search (ENAS) achieves novel efficiency for learning
architecture with high-performance via parameter sharing and reinforcement learning (RL) …
architecture with high-performance via parameter sharing and reinforcement learning (RL) …
Heuristic rank selection with progressively searching tensor ring network
Recently, tensor ring networks (TRNs) have been applied in deep networks, achieving
remarkable successes in compression ratio and accuracy. Although highly related to the …
remarkable successes in compression ratio and accuracy. Although highly related to the …
A novel convolutional neural network based architecture for object detection and recognition with an application to traffic sign recognition from road scenes
Object detection and recognition is a significant activity in computer vision applications.
Advanced driver assistance systems (ADAS) uses computer vision predominantly as its tool …
Advanced driver assistance systems (ADAS) uses computer vision predominantly as its tool …
Active learning-based pedestrian and road sign detection
For autonomous driving, pedestrian and road signs detection are key elements. There is
much existing literature available addressing this issue successfully. However, the …
much existing literature available addressing this issue successfully. However, the …