Attention-CARU With Texture-Temporal Network for Video Depth Estimation by Sio-Kei Im, Ka-Hou Chan

“…RNN-based encoder-decoder architectures are the most commonly used methods for depth feature prediction, but recurrent operators have limitations of large-scale perspective from global information and also face the long-term dependency problem, which often leads to inaccurate prediction of object depth in complex scenes. …”
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Deep Learning Enabled Fault Diagnosis Using Time-Frequency Image Analysis of Rolling Element Bearings by David Verstraete, Andrés Ferrada, Enrique López Droguett, Viviana Meruane, Mohammad Modarres

“…This knowledge is sometimes a luxury and could introduce added uncertainty and bias to the results. To address this problem a deep learning enabled featureless methodology is proposed to automatically learn the features of the data. …”
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SwinConvNeXt: a fused deep learning architecture for Real-time garbage image classification by B. Madhavi, Mohan Mahanty, Chia-Chen Lin, B. Omkar Lakshmi Jagan, Hari Mohan Rai, Saurabh Agarwal, Neha Agarwal

“…These limitations generate various challenges in effectively capturing and representing the nuanced features of visually similar objects. To address this problem, we proposed the stacking of an enhanced Swin Transformer, improved ConvNeXt, and a spatial attention mechanism. …”
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CME Velocity Field Calculation Model Based on an Unsupervised Transformer Optical Flow Network by Qingyang Chen, Hong Lin, Zhenping Qiang, Hui Liu, Kaifan Ji, Zhenhong Shang

“…Fluctuations in exposure time and the influence of space weather will lead to inconsistent brightness of the same feature point at different times. To address this problem, we propose an unsupervised multiscale optical flow network based on Vision Transformer, named UTFlowNet. …”
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An Enhanced Human Evolutionary Optimization Algorithm for Global Optimization and Multi-Threshold Image Segmentation by Liang Xiang, Xiajie Zhao, Jianfeng Wang, Bin Wang

“…Thresholding image segmentation aims to divide an image into a number of regions with different feature attributes in order to facilitate the extraction of image features in the context of image detection and pattern recognition. …”
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Research on Small-Sample Credit Card Fraud Identification Based on Temporal Attention-Boundary-Enhanced Prototype Network by Boyu Liu, Longrui Wu, Shengdong Mu

“…In this paper, we propose a credit card fraud detection method called the Time-Series Attention-Boundary-Enhanced Prototype Network (TABEP), which strengthens the temporal feature dependency between channels by incorporating a time-series attention module to achieve channel temporal fusion feature acquisition. …”
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Parameter Identification and Transition Process Online Calibration Method of Pulsed Eddy Current Receiving Coil Based on Underdamped Dynamic Response Characteristics by Zhiwu Zeng, Jie Wang, Xiaoju Huang, Yun Zuo, Yuan Liu, Xu Tian, Feng Pei, Kui Liu, Fu Chen, Xiaotian Wang, Jingang Wang

“…In order to solve the problem that the system parameters will be offset during the detection process of the pulsed eddy current receiving coil, this paper first analyzes the response signal of the receiving system and the deconvolution process of the response signal, and discusses the influence of various system parameters on the deconvolution accuracy. …”
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Multiradar Collaborative Task Scheduling Algorithm Based on Graph Neural Networks with Model Knowledge Embedding by Haoqing LI, Dian YU, Changchun PAN, Wenxian YU, Dongying LI

“…However, their efficiency is heavily dependent on effectively extracting the key features of the problem. The ability to quickly and comprehensively extract common features of multiradar scheduling problems is essential for improving the efficiency of such AI scheduling algorithms. …”
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High-Voltage CVT Fault Diagnosis Based on Effective Data Recognition and Multi-dimensional Information Fusion by Huishan ZHANG

“…To address the prevalent problem in current high-voltage CVT fault diagnosis, such as limited information sources, poor accuracy, and significant interference in partial discharge devices leading to compromised fault signal detection and accuracy, a fault diagnosis method based on multi-dimensional information fusion is proposed. …”
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An MCMC Approach to Bayesian Image Analysis in Fourier Space by Konstantinos Bakas, John Kornak, Hernando Ombao

“…Bayesian image analysis methods are commonly applied to solve image analysis problems such as noise reduction, feature enhancement, and object detection. …”
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Intelligent recognition technology of high speed moving target contour in dynamic visual scene by Min Qiu

“…On the basis of extracting edge contours, the contour description method based on the increment of centroid height is used to extract the feature of contour centroid height increment, which not only considers the problem of motion blur but also incorporates the dynamic information of contour changes with target motion. …”
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Dynamic risk prediction in financial-production systems using temporal self-attention and adaptive autoregressive models by Xuduo Lin, Ziang Qi 

“…To address this, we propose an innovative hybrid temporal model, TSA-AR (Temporal Self-Attention Adaptive Autoregression), which combines temporal self-attention mechanisms with an adaptive autoregressive model to solve the risk prediction problem in financial and production systems. TSA-AR performs multi-scale feature extraction through an improved Informer encoder, dynamically adjusts model parameters with a dynamic autoregressive module, and constructs the nonlinear dependencies between financial and production systems through a cross_modal interaction graph. …”
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Enhanced U-Net with Multi-Module Integration for High-Exposure-Difference Image Restoration by Bo-Lin Jian, Hong-Li Chang, Chieh-Li Chen

“…This study adopts supervised learning to solve the problem of images under lighting discrepancies using a U-Net as our main architecture of the network and adding suitable modules to its encoder and decoder, such as inception-like blocks, dual attention units, selective kernel feature fusion, and denoising blocks. …”
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A Holistic Strategy of Modified Superpixel Segmentation and Randomized Adam Hyperparameter Tuning with Deep Learning Approaches for the Classification of Breast Cancer from BreakHi... by Gowri Shankar Manivannan, Karthikeyan Shanmugam, Harikumar Rajaguru, Satish V. Talawar, Rajanna Siddaiah

“…In this study, an integrated breast cancer detection approach using BreakHis images is proposed focusing on balanced accuracy rate analysis to solve imbalanced datasets problem. …”
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Advancing smart communities with a deep learning framework for sustainable resource management. by Yongyan Zhao

“…The framework leverages long short-term memory (LSTM) networks for temporal data, convolutional neural networks (CNNs) for spatial analysis, and autoencoders for anomaly detection. The system focuses on two main objectives, which include better forecasting precision, optimum resource distribution, and efficient detection of operational problems.…”
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ADWNet: An improved detector based on YOLOv8 for application in adverse weather for autonomous driving by Xinyun Feng, Tao Peng, Ningguo Qiao, Haitao Li, Qiang Chen, Rui Zhang, Tingting Duan, JinFeng Gong

“…To address the problem of information loss in fused features, Neck has been replaced with RepGDNeck. …”
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Research on Visual SLAM Navigation Techniques for Dynamic Environments by Tongjun Wang, Peijun Zhao

“…Aiming at the inconsistency between the direction of dynamic objects and static background optical flow, this method adopts a high-real-time dynamic region mask detection algorithm to eliminate the feature points in the dynamic region mask, remove the camera motion optical flow according to the original feature information, and then cluster the optical flow amplitude of dynamic objects so as to realize the dynamic region mask detection and eliminate the dynamic signpost points combined with the polar geometric constraints. …”
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Evaluating the performance of pixel-based and object-based multidimensional clustering algorithms for automated surface water mapping by Bohao Li, Kai Liu, Ming Wang, Yanfang Wang, Linmei Zhuang, Weihua Zhu, Chenxia Li, Linhao Zhang, Yanan Chen

“…Unsupervised classification holds promise for automating large-scale surface water detection, and it helps solve the difficult problem of sample collection in supervised classification. …”
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A Weighted-Transfer Domain-Adaptation Network Applied to Unmanned Aerial Vehicle Fault Diagnosis by Jian Yang, Hairong Chu, Lihong Guo, Xinhong Ge

“…The method is based on unsupervised transfer learning, which can transfer the knowledge learnt from existing datasets to solve problems in the target domain. The method contains three novel multiscale modules: a feature extractor, used to extract multidimensional features from the input; a domain discriminator, used to improve the imbalance of the data distribution between the source domain and the target domain; and a label classifier, used to classify data categories for the target domain. …”
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GS-GVINS: A Tightly-Integrated GNSS-Visual-Inertial Navigation System Augmented by 3D Gaussian Splatting by Zelin Zhou, Shichuang Nie, Saurav Uprety, Hongzhou Yang

“…However, most integrated systems rely on feature-tracking based visual odometry, which suffers from the problem of feature sparsity, high dynamics, significant illumination changes, etc. …”
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