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In this paper, we propose a novel object detection algorithm named "Deep Regionlets" by integrating deep neural networks and conventional detection schema for accurate generic object detection. Motivated by the advantages of regionlets on modeling object deformation and multiple aspect ratios, we incorporate regionlets into an end-to-end trainable deep learning framework. The deep regionlets framework consists of a region selection network and a deep regionlet learning module. Specifically, given a detection bounding box proposal, the region selection network provides guidance on where to select sub-regions from which features can be learned from. An object proposal typically contains 3-16 sub-regions. The regionlet learning module focuses on local feature selection and transformation to alleviate the effects of appearance variations. To this end, we first realize non-rectangular region selection within the detection framework to accommodate variations in object appearance. Moreover, we design a "gating network" within the regionlet leaning module to enable instance dependent soft feature selection and pooling. The Deep Regionlets framework is trained end-to-end without additional efforts. We present ablation studies and extensive experiments on the PASCAL VOC dataset and the Microsoft COCO dataset. The proposed method outperforms state-of-the-art algorithms, such as RetinaNet and Mask R-CNN, even without additional segmentation labels.
This article was published in the following journal.
Name: IEEE transactions on pattern analysis and machine intelligence
Representation learning is a fundamental but challenging problem, especially when the distribution of data is unknown. In this paper, we propose a new representation learning method, named Structure T...
This paper argues that Brain-Inspired Spiking Neural Network (BI-SNN) architectures can learn and reveal deep in time-space functional and structural patterns from spatio-temporal data. These patterns...
3D reconstruction is a longstanding ill-posed problem, which has been explored for decades by the computer vision, computer graphics, and machine learning communities. Since 2015, image-based 3D recon...
A deep learning approach has been taken to improve detection characteristics of surface plasmon microscopy (SPM) of light scattering. Deep learning based on convolutional neural network algorithm was ...
Deep learning with convolutional neural networks (CNN) is a rapidly advancing subset of artificial intelligence that is ideally suited to solving image-based problems. There are an increasing number o...
Artificial Intelligence and Machine Learning techniques may provide insight into exploring the potential covert association behind and reveal some early ocular architecture changes in indi...
The object of this study is to longitudinally collect clinical outcomes of patients receiving deep brain stimulation for movement disorders with the objective of making retrospective compa...
It has been widely accepted that a split of the deep temporal fascia occurs approximately 2 to 3 cm above the zygomatic arch, named the superficial and deep layers. The deep layer of the d...
CT-guided epidural steroid injection (ESI) thrives among interventional radiologists. Although X-ray fluoroscopy still remains as the gold standard to guide ESI, CT guidance has the merits...
The aim of this study was to assess the effect of a blended-learning model on physiotherapy students´ attitude, knowledge and opinions towards learning professional ethics. A simple-blin...
DEEP VEIN THROMBOSIS of an upper extremity vein (e.g., AXILLARY VEIN; SUBCLAVIAN VEIN; and JUGULAR VEINS). It is associated with mechanical factors (Upper Extremity Deep Vein Thrombosis, Primary) secondary to other anatomic factors (Upper Extremity Deep Vein Thrombosis, Secondary). Symptoms may include sudden onset of pain, warmth, redness, blueness, and swelling in the arm.
A space which has limited openings for entry and exit combined with unfavorable natural ventilation such as caves, refrigerators, deep tunnels, pipelines, sewers, silos, tanks, vats, mines, deep trenches or pits, vaults, manholes, chimneys, etc.
An important nosocomial fungal infection with species of the genus CANDIDA, most frequently CANDIDA ALBICANS. Invasive candidiasis occurs when candidiasis goes beyond a superficial infection and manifests as CANDIDEMIA, deep tissue infection, or disseminated disease with deep organ involvement.
Process in which individuals take the initiative, in diagnosing their learning needs, formulating learning goals, identifying resources for learning, choosing and implementing learning strategies and evaluating learning outcomes (Knowles, 1975)
Disease involving the common PERONEAL NERVE or its branches, the deep and superficial peroneal nerves. Lesions of the deep peroneal nerve are associated with PARALYSIS of dorsiflexion of the ankle and toes and loss of sensation from the web space between the first and second toe. Lesions of the superficial peroneal nerve result in weakness or paralysis of the peroneal muscles (which evert the foot) and loss of sensation over the dorsal and lateral surface of the leg. Traumatic injury to the common peroneal nerve near the head of the FIBULA is a relatively common cause of this condition. (From Joynt, Clinical Neurology, 1995, Ch51, p31)
A generic drug (generic drugs, short: generics) is a drug defined as "a drug product that is comparable to brand/reference listed drug product in dosage form, strength, route of administration, quality and performance characteristics, and intended u...
Clinical Approvals Clinical Trials Drug Approvals Drug Delivery Drug Discovery Generics Drugs Prescription Drugs In the fields of medicine, biotechnology and pharmacology, drug discovery is the process by which drugs are dis...