A novel lightweight 3D CNN for accurate deformation time series retrieval in MT-InSAR by Mahmoud Abdallah, Xiaoli Ding, Samaa Younis, Songbo Wu

“…We also developed a separable convolution operator to reduce the computational costs without compromising performance. …”
Get full text

Intelligent Identification of Tea Plant Seedlings Under High-Temperature Conditions via YOLOv11-MEIP Model Based on Chlorophyll Fluorescence Imaging by Chun Wang, Zejun Wang, Lijiao Chen, Weihao Liu, Xinghua Wang, Zhiyong Cao, Jinyan Zhao, Man Zou, Hongxu Li, Wenxia Yuan, Baijuan Wang

“…First, to reduce the number of network parameters and maintain a low computational cost, the lightweight MobileNetV4 network was introduced into the YOLOv11 model as a new backbone network. …”
Get full text

SYNTHESIS OF MOBILE OBJECTS COMPROMISABLE OPTIMAL TRAJECTORIES IN THE CONFLICT ENVIRONMENT by Albert M. Voronin, Yurii K. Ziatdinov, Oleksandr Y. Permiakov, Ihor D. Varlamov

“…The opposite optimization problem of active conflict subjects placement suggests that the mobile object motion to the target endpoint is maximum hampered, and the cost spending for system operation is minimized. …”
Get full text

LPFFNet: Lightweight Prior Feature Fusion Network for SAR Ship Detection by Xiaozhen Ren, Peiyuan Zhou, Xiaqiong Fan, Chengguo Feng, Peng Li

“…In addition, the enhanced ghost convolution (EGConv) is used to generate more reliable gradient information. …”
Get full text

Twofold dynamic attention guided deep network and noise-aware mechanism for image denoising by Zihao Chen, Alex Noel Joseph Raj, Vijayarajan Rajangam, Wei Li, Vijayalakshmi G.V. Mahesh, Zhemin Zhuang

“…Convolutional neural networks are given extensive attention towards noise removal due to their good performance over traditional denoising algorithms. …”
Get full text

U-shape-based network for left ventricular segmentation in echocardiograms with contrastive pretraining by Zhengkun Qian, Tao Hu, Jianming Wang, Zizhong Yang

“…Extensive experimental results on the EchoNet-Dynamic dataset demonstrate that the proposed modifications deliver competitive performance at a lower computational cost.…”
Get full text

3D Object Detection Based on Graph Network Fusion Sampling Strategy by LI Wenju, CHEN Zhilin, QU Jiantao, CUI Liu, CHU Wanghui, GAO Hui

“…In the 3D target detection technology based on point cloud, there are problems like high cost of point cloud calculation and large gap between target scales, which lead to low target detection efficiency. …”
Get full text

A Small-Sample Target Detection Method of Side-Scan Sonar Based on CycleGAN and Improved YOLOv8 by Ye Zheng, Jun Yan, Junxia Meng, Ming Liang

“…Because of their low cost and ease of deployment, side-scan sonars is one of the most widely used underwater survey instruments. …”
Get full text

LPCF-YOLO: A YOLO-Based Lightweight Algorithm for Pedestrian Anomaly Detection with Parallel Cross-Fusion by Peiyi Jia, Hu Sheng, Shijie Jia

“…Additionally, an ADown module is introduced in the third layer to reduce the computational cost. In the neck network, a Lightweight High-level Screening Feature Pyramid Network (L-HSFPN) is designed to replace the PAFPN structure. …”
Get full text

Tuberculosis detection with customized CNN and oversampling techniques: a deep learning approach by B. H. Shekar, Shazia Mannan

“…In this regard, an automated system that can analyse and diagnose pulmonary TB by using Chest X-Rays (CXR) can prove to be a cost effective, dependable and quick alternative to manual diagnostic methods. …”
Get full text

High-Accuracy Recognition Method for Diseased Chicken Feces Based on Image and Text Information Fusion by Duanli Yang, Zishang Tian, Jianzhong Xi, Hui Chen, Erdong Sun, Lianzeng Wang

“…Key innovations include the following: (1) Integrating MASA(Manhattan self-attention)and DSconv (Depthwise Separable convolution) into the backbone network to mitigate feature confusion. (2) Utilizing a pre-trained BERT to extract textual semantic features, reducing annotation dependency and cost. (3) Designing a lightweight Gated Cross-Attention (GCA) module for dynamic multimodal fusion, achieving a 41% parameter reduction versus cross-modal transformers. …”
Get full text

A Power-Efficient 0.5668 TOPS/W Digital Logic Accelerator Implemented Using 40-nm CMOS Process for Underwater Object Recognition Usage by Chua-Chin Wang, Shih-Heng Luo, Hsin-Che Wu, Ralph Gerard B. Sangalang, Chewn-Pu Jou, Harry Hsia, Lan-Chou Cho

“…DNN (deep neural network) and CNN (convolution neural network) have been widely used in real-time artificial intelligent (AI) applications, particularly image or video recognitions, because they have been proved physically in many occasions. …”
Get full text

BG-YOLO: A Bidirectional-Guided Method for Underwater Object Detection by Ruicheng Cao, Ruiteng Zhang, Xinyue Yan, Jian Zhang

“…During the detection tasks, only the object detection branch is reserved so that no additional computational cost is introduced. Extensive experiments demonstrate that the proposed method significantly improves the detection performance of the YOLOv5s object detection network (the mAP is increased by up to 2.9%) and maintains the same inference speed as YOLOv5s (132 fps).…”
Get full text

Enhancing Speaker Recognition with CRET Model: a fusion of CONV2D, RESNET and ECAPA-TDNN by Pinyan Li, Lap Man Hoi, Yapeng Wang, Xu Yang, Sio Kei Im

“…Although the Emphasized Channel Attention, Propagation, and Aggregation in Time Delay Neural Network (ECAPA-TDNN) model can obtain temporal context information through dilated convolution to some extent, this model falls short in acquiring fully comprehensive speech features. …”
Get full text

YOLOv10-kiwi: a YOLOv10-based lightweight kiwifruit detection model in trellised orchards by Jie Ren, Wendong Wang, Yuan Tian, Jinrong He

“…Second, to further reduce model complexity, a novel C2fDualHet module is proposed by integrating two consecutive Heterogeneous Kernel Convolution (HetConv) layers as a replacement for the traditional Bottleneck structure. …”
Get full text

Edge Artificial Intelligence: Real-Time Noninvasive Technique for Vital Signs of Myocardial Infarction Recognition Using Jetson Nano by H. M. Mohan, S. Anitha, Rifai Chai, Sai Ho Ling

“…We propose a model, which is cost-effective and consumes low power for onboard detection of vital signs of myocardial infarction and evaluated the metrics to achieve a mean average precision of 76.4% and an average recall of 80%.…”
Get full text

Deep vision-based real-time hand gesture recognition: a review by Cui Cui, Mohd Shahrizal Sunar, Goh Eg Su

“…However, some issues remain in edge blurring generated by complex backgrounds, rotation inaccuracy induced by fast movement, and delay caused by computing cost. Recently, the emergence of deep learning has ameliorated these issues, convolution neural network (CNN) enhanced edge clarity, long-short term memory (LSTM) improved rotation accuracy, and attention mechanism optimized response time. …”
Get full text

PPLA-Transformer: An Efficient Transformer for Defect Detection with Linear Attention Based on Pyramid Pooling by Xiaona Song, Yubo Tian, Haichao Liu, Lijun Wang, Jinxing Niu

“…Our model demonstrates satisfactory performance with minimal computational cost. It outperforms Swin-Transformer by 1.2% mAP and 52 FPS on the self-constructed SIM card slot defect dataset. …”
Get full text

ST-YOLO: A defect detection method for photovoltaic modules based on infrared thermal imaging and machine vision technology. by Hanfei Xie, Baoxi Yuan, Chengyu Hu, Yujie Gao, Feng Wang, Chunlan Wang, Yuqian Wang, Peng Chu

“…First, it introduces the C2f-SCconv convolution module, which is based on SCconv convolution. …”
Get full text

Research on Underwater Echo Generation Method Based on Small Sample by Chen-yu WANG, Li-wen LIU, Gang LIU, Bo LI, Yun-chuan YANG

“…However, obtaining underwater sample data from actual scientific research is extremely difficult because of environmental constraints, time, cost, and other factors. An insufficient number of samples leads to poor training effects in deep learning models. …”
Get full text