Maintenance of railroad track safety is of utmost importance as derailment accidents cause significant loss to life and property. Inspection of railroad tracks and their components is necessary in order to ensure security and well-being of goods ...

The unmonitored jellyfish boom inevitably destroys coastal biodiversities as a type of planktons with extremely high fecundity. It even seriously endangers people’s economic and social activities, such as clogging the water intake system of ...

The application of object detectors contributes to the monitoring and protection of wildlife with high accuracy and fast speed. However, the variety of shapes and appearances of wildlife bring difficulties to the detection task, which requires the ...

The fluctuation of the bird population reflects the change in the ecosystem, which plays a vital role in ecosystem conservation. However, manual counting is still the mainstream method for bird population counting, which is time-consuming and ...

Fire and smoke object detection is of great significance due to the extreme destructive power of fire disasters. Most of the existing methods, whether traditional computer vision-based models with sensors or deep learning-based models have ...

Lane detection models based deep semantic segmentation often fail in challenging scenarios for lacking enough contextual information. In this paper, we first point out that a soft label extracted from a trained semantic segmentation model is ...

Face detection and recognition are the most substantial research areas in computer vision and transfer learning due to the inspiring nature of faces as an object. In this paper, we show that we can obtain promising results on the standard face ...

Convolutional Neural Network (CNN) has been widely used in various tasks of computer vision. For contour detection, the encoding network and decoding network structure are mainly used. The encoding network mainly uses existing networks such as VGG,...

The traditional welding spots detection methods are very sensitive to light pollution, rust and oil stain. In this work, a novel method that combines light-weight deep learning model and circle detection algorithm for welding spots detection is ...

Traditional U-Net framework generates multi-level features by the successive convolution and pooling operations, and then decodes the saliency cue by progressive upsampling and skip connection. The multi-level features are generated from the same ...

The increasing frequency of skin tumour across the globe and their timely diagnosis is one of the most promising research directions in the healthcare domain. The most important cause behind the skin cancer mortalities is delayed detection. Early ...

Though the standard convolutional neural networks (CNNs) have been proposed to increase the robustness of facial action unit (AU) detection regarding pose variations, it is hard to enhance detection performance because the standard CNNs are not ...

As a general trend, unmanned ships have been gradually replacing humans and served as the cleaner of lakes. To work properly, those unmanned ships need to detect and localize lake floating objects that need to be collected. Compared to ...

We combine SNet network based on gating mechanism with poolnet network to solve the problem of salient object detection. The network construction of this paper is based on FPN, which is a classic U-net backbone network. Inspired by poolnet, we ...

Difference between similar feature points is presented in the fine-grained classification, which depends on discriminative in extremely localized regions. Hence, the accurate localization of discriminative regions is the major challenge found in ...

Diagnosis of Glaucoma eye disease is a challenging task for CADx (computer-aided diagnostics) systems. An automatic CADx framework is developed for diagnosing glaucoma eye disease by handcrafted feature-based segmentation in retinal images. In ...

Developing automated systems to detect and track on-road vehicles is a demanding research area in Intelligent Transportation System (ITS). This article proposes a method for on-road vehicle detection and tracking in varying weather conditions ...

Fruit detection plays a vital role in robotic harvesting platforms. However, natural scene attributes such as illumination variation, branch and leaf occlusion, clusters of tomatoes, shading, etc. and double scene including image augmentation and ...

In this paper, a Deep Convolution Neural Network (CNN) based Super-Resolution (SR) decision-making tool is proposed for the raw panchromatic satellite image. Conventionally, human visual interpretation through spotting recognizable objects and ...

Infrared small target detection (ISTD) is a critical technique in both civil and military applications such as leak and defect inspection, cell segmentation for medicine analysis, early-warning systems and so on. Over the last decade, numerous ...