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Recent advances in deep learning for object detection
Object detection is a fundamental visual recognition problem in computer vision and has
been widely studied in the past decades. Visual object detection aims to find objects of …
been widely studied in the past decades. Visual object detection aims to find objects of …
Intelligent small object detection for digital twin in smart manufacturing with industrial cyber-physical systems
Recently, along with several technological advancements in cyber-physical systems, the
revolution of Industry 4.0 has brought in an emerging concept named digital twin (DT), which …
revolution of Industry 4.0 has brought in an emerging concept named digital twin (DT), which …
Reverse attention for salient object detection
Benefit from the quick development of deep learning techniques, salient object detection has
achieved remarkable progresses recently. However, there still exists following two major …
achieved remarkable progresses recently. However, there still exists following two major …
Ubernet: Training a universal convolutional neural network for low-, mid-, and high-level vision using diverse datasets and limited memory
In this work we train in an end-to-end manner a convolutional neural network (CNN) that
jointly handles low-, mid-, and high-level vision tasks in a unified architecture. Such a …
jointly handles low-, mid-, and high-level vision tasks in a unified architecture. Such a …
Holistically-nested edge detection
We develop a new edge detection algorithm that addresses two critical issues in this long-
standing vision problem:(1) holistic image training; and (2) multi-scale feature learning. Our …
standing vision problem:(1) holistic image training; and (2) multi-scale feature learning. Our …
CrackFormer network for pavement crack segmentation
In this paper, we rethink our earlier work on self-attention based crack segmentation, and
propose an upgraded CrackFormer network (CrackFormer-II) for pavement crack …
propose an upgraded CrackFormer network (CrackFormer-II) for pavement crack …
Dynamic feature integration for simultaneous detection of salient object, edge, and skeleton
Salient object segmentation, edge detection, and skeleton extraction are three contrasting
low-level pixel-wise vision problems, where existing works mostly focused on designing …
low-level pixel-wise vision problems, where existing works mostly focused on designing …
RoadNet: Learning to comprehensively analyze road networks in complex urban scenes from high-resolution remotely sensed images
It is a classical task to automatically extract road networks from very high-resolution (VHR)
images in remote sensing. This paper presents a novel method for extracting road networks …
images in remote sensing. This paper presents a novel method for extracting road networks …
Traffic sign detection and recognition using fully convolutional network guided proposals
Detecting and recognizing traffic signs is a hot topic in the field of computer vision with lots of
applications, eg, safe driving, path planning, robot navigation etc. We propose a novel …
applications, eg, safe driving, path planning, robot navigation etc. We propose a novel …
Decomposition and completion network for salient object detection
Recently, fully convolutional networks (FCNs) have made great progress in the task of
salient object detection and existing state-of-the-arts methods mainly focus on how to …
salient object detection and existing state-of-the-arts methods mainly focus on how to …