Search Results - "((\"Encoder–decoder architecture\") OR (\"Encoder–design architecture\"))~"

Inception UNet architecture for breast tumor segmentation and detection using hybrid deep learning approach.

Authors: Sharma, Ajay Mishra, Pramod Kumar

Source: Multimedia Tools & Applications; Jul2025, Vol. 84 Issue 24, p28225-28263, 39p

Subject Terms: BREAST cancer, DEEP learning, TUMOR classification, TRANSFER of training, INTERDISCIPLINARY research, FEATURE extraction, ULTRASONIC imaging, EARLY diagnosis

SCTNet-NAS: efficient semantic segmentation via neural architecture search for cloud-edge collaborative perception.

Authors: Liu, Ruyu Wang, Lin Yu, Zhihao et al.

Source: Complex & Intelligent Systems; Aug2025, Vol. 11 Issue 8, p1-16, 16p

DUC-Net: A deep unified cross-modal architecture with cascaded feature learning for medical image segmentation.

Authors: Memon, Yumna Zeng, Feng Khawaja, Faiza Riaz

Source: Cluster Computing; Dec2025, Vol. 28 Issue 16, p1-26, 26p

An Efficient Vision Mamba–Transformer Hybrid Architecture for Abdominal Multi-Organ Image Segmentation.

Authors: Lu, Fang Xu, Jingyu Sun, Qinxiu et al.

Source: Sensors (14248220); Nov2025, Vol. 25 Issue 21, p6785, 18p

Subject Terms: DEEP learning, TRANSFORMER models, IMAGE processing, DIAGNOSIS, COMPUTER-assisted image analysis (Medicine)

Enhanced encoder–decoder architecture for visual perception multitasking of autonomous driving.

Authors: Usman, Muhammad Zaka-Ud-Din, Muhammad Ling, Qiang

Source: Expert Systems with Applications. Jul2024, Vol. 246, pN.PAG-N.PAG. 1p.

Subject Terms: *CONVOLUTIONAL neural networks, *AUTONOMOUS vehicles, *OBJECT recognition (Computer vision), *TRANSFORMER models, *VISUAL perception, *COMPUTER multitasking, *VIDEO coding, *SOURCE code

Exploring the Use of Deep Learning Models for Image Compression in Embedded Systems: Encoder and Decoder Architectures.

Authors: Potlapalli, Abhiram Khetavath, Seetharam

Source: Journal of Intelligent Systems & Internet of Things; 2025, Vol. 15 Issue 1, p37-52, 16p

Subject Terms: CONVOLUTIONAL neural networks, IMAGE processing, JPEG (Image coding standard), DEEP learning, ALGORITHMS, IMAGE compression, INSTRUCTIONAL systems

Research on multi-scenario adaptive acoustic encoders based on neural architecture search.

Authors: Wu, Yiliang Luo, Xuliang Guo, Fengchan et al.

Source: Frontiers in Physics; 2024, p1-13, 13p

Subject Terms: AUTOMATIC speech recognition, SPEECH perception, SPEECH, SOUND design, ERROR rates

MambaSegNet: A Fast and Accurate High-Resolution Remote Sensing Imagery Ship Segmentation Network.

Authors: Wen, Runke Yuan, Yongjie Xu, Xingyuan et al.

Source: Remote Sensing; Oct2025, Vol. 17 Issue 19, p3328, 27p

Subject Terms: HIGH resolution imaging, IMAGE segmentation, REMOTE sensing, FEATURE extraction, ACQUISITION of data

MMFNet: A Mamba-Based Multimodal Fusion Network for Remote Sensing Image Semantic Segmentation.

Authors: Qiu, Jingting Chang, Wei Ren, Wei et al.

Source: Sensors (14248220); Oct2025, Vol. 25 Issue 19, p6225, 21p

Subject Terms: REMOTE sensing, IMAGE segmentation, DIGITAL elevation models, CONVOLUTIONAL neural networks

CSI-Net: CNN Swin Transformer Integrated Network for Infrared Small Target Detection.

Authors: Choi, Lammi Chung, Won Young Park, Chan Gook

Source: International Journal of Control, Automation & Systems; Sep2024, Vol. 22 Issue 9, p2899-2908, 10p

GOFENet: A Hybrid Transformer–CNN Network Integrating GEOBIA-Based Object Priors for Semantic Segmentation of Remote Sensing Images.

Authors: He, Tao Chen, Jianyu Pan, Delu

Source: Remote Sensing; Aug2025, Vol. 7 Issue 15, p2652, 29p

Subject Terms: REMOTE sensing, IMAGE segmentation, TRANSFORMER models, CONVOLUTIONAL neural networks, IMAGE analysis, DEEP learning, SPATIAL analysis (Statistics)

Developing Interpretable Deep Learning Model for Subtropical Forest Type Classification Using Beijing-2, Sentinel-1, and Time-Series NDVI Data of Sentinel-2.

Authors: Chen, Shudan Wang, Xuefeng Shi, Mengmeng et al.

Source: Forests (19994907); Nov2025, Vol. 16 Issue 11, p1709, 21p

Subject Terms: DEEP learning, REMOTE sensing, NORMALIZED difference vegetation index, FOREST site quality, ENVIRONMENTAL monitoring

Enhancing hyperkinetic dysarthria speech recognition through deep cascade convolution and integrated attention mechanism.

Authors: Mahamudul Hashan, Antor

Source: International Journal of Speech Technology; Sep2025, Vol. 28 Issue 3, p699-707, 9p

Subject Terms: DYSARTHRIA, DEEP learning, TRANSCRIPTION (Linguistics), ERROR rates, SPEECH perception, MACHINE learning, HEALTH care industry

Company/Entity: DCC PLC

DCM-Net: dual-encoder CNN-Mamba network with cross-branch fusion for robust medical image segmentation.

Authors: Atabansi, Chukwuemeka Clinton Wang, Sheng Li, Hui et al.

Source: BMC Medical Imaging; 9/29/2025, Vol. 25 Issue 1, p1-24, 24p

Subject Terms: IMAGE segmentation, TUMOR diagnosis, DEEP learning

Multimodal Artificial Intelligence in Medical Diagnostics.

Authors: Jandoubi, Bassem Akhloufi, Moulay A.

Source: Information; Jul2025, Vol. 16 Issue 7, p591, 34p

Subject Terms: CLINICAL decision making, ARTIFICIAL intelligence, MACHINE learning, ELECTRONIC health records, TRANSFORMER models, DEEP learning

An efficient architecture implementation of a golay code encoder in CMOS 45nm technology.

Authors: Kumar, Dhanavath Rupa Naik, Gopiya Naik Sevya

Source: AIP Conference Proceedings; 2024, Vol. 2492 Issue 1, p1-12, 12p

Subject Terms: BINARY codes, TELECOMMUNICATION systems, VIDEO coding, DIGITAL communications

FlowNAS: Neural Architecture Search for Optical Flow Estimation.

Authors: Lin, Zhiwei Liang, Tingting Xiao, Taihong et al.

Source: International Journal of Computer Vision; Apr2024, Vol. 132 Issue 4, p1055-1074, 20p

Subject Terms: OPTICAL flow, IMAGE recognition (Computer vision), FEATURE extraction, EVOLUTIONARY algorithms, VIDEO coding, SOURCE code

Attention-guided fusion of transformers and CNNs for enhanced medical image segmentation.

Authors: Zhou, Shiyao Wang, Mengyao Huang, Zhiyong et al.

Source: Visual Computer; Oct2025, Vol. 41 Issue 13, p10577-10597, 21p

Subject Terms: TRANSFORMER models, CONVOLUTIONAL neural networks, COMPUTER-assisted image analysis (Medicine), MACHINE learning

DMA-Net: Dynamic Morphology-Aware Segmentation Network for Remote Sensing Images.

Authors: Deng, Chao Liang, Haojian Qin, Xiao et al.

Source: Remote Sensing; Jul2025, Vol. 17 Issue 14, p2354, 30p

Subject Terms: REMOTE-sensing images, IMAGE segmentation, FEATURE extraction, DEEP learning, ARTIFICIAL neural networks, TRANSFORMER models

混凝土桥梁整体表观多缺陷图像精细分割方法.

Alternate Title: Fine-grained image segmentation method for holistic surface multi-defects in concrete bridges.

Authors: 周勇军 罗 楠 孙延晨 et al.

Source: Journal of Harbin Institute of Technology. Social Sciences Edition / Haerbin Gongye Daxue Xuebao. Shehui Kexue Ban. Jun2025, Vol. 57 Issue 6, p103-115. 13p.

Subject Terms: Bridge defects, Drone aircraft, Concrete bridges, Surface defects, Erosion