Results (15)
Search Parameters:
Keyword: Object DetectionTowards Real-Time Multi-Class Object Detection and Tracking for the FLS Pattern Cutting Task
The advent of laparoscopic surgery has increased the need to incorporate simulator-based training into traditional training programs to improve resident training and feedback. However, current training methods rely on expert surgeons to evaluate the dexterity of trainees, a time-consuming and subjective process. Through this research, we aim to extend the use of object detection in…
Read MoreCombination of Salient Object Detection and Image Matching for Object Instance Recognition
Object Instance Recognition aims to classify objects specifically and usually use a single reference image. It is possible to be used in many applications such as visual search, information retrieval and augmented reality. However, various things affect the appearance of the objects, which makes the recognition process harder, especially if a single reference image is…
Read MoreNorthern Leaf Blight and Gray Leaf Spot Detection using Optimized YOLOv3
Corn is one of the most important agricultural products in the world. However, climate change greatly threatens corn yield, further increasing already prevalent diseases. Northern corn leaf blight (NLB) and Gray Leaf Spot are two major corn diseases with lesion symptoms that look very similar to each other, and can lead to devastating loss if…
Read MoreConvolutional Neural Network Based on HOG Feature for Bird Species Detection and Classification
This work is concerned with the detection and classification of birds that have applications like monitoring extinct and migrated birds. Recent computer vision algorithms can precise this kind of task but still there are some dominant issues like low light, very little differences between subspecies of birds, etc are to be studied. As Convolution Neural…
Read MoreVisual Saliency Detection using Seam and Color Cues
Human have the god gifted ability to focus on the essential part of a visual scenery irrespective of its background. This important area is called the salient region of an image. Computationally achieving this natural human quality is an attractive goal of today’s scientific world. Saliency detection is the technique of finding the salient region…
Read MoreAn Enhanced Artificial Intelligence-Based Approach Applied to Vehicular Traffic Signs Detection and Road Safety Enhancement
The paper treats a problem for detection and recognition objects in computer vision sector, where researchers recommended OpenCV software and development tool, it’s several and better-remembered library resource for isolating, detecting, and recognition of particular objects, what we would find an appropriate system for detecting and recognition traffic roads signs. The robustness with optimization is…
Read MoreFeature Gate Computational Top-Down Model for Target Detection
Computer vision is a technique used for processing images and videos which are increasingly becoming ubiquitous day by day. Technologies developed are revolving around human needs and demands high computational power as volume of data increases. The extraction of the necessary information for processing, that is independent of various scene complexity is a challenging task.…
Read MoreReal-Time Traffic Sign Detection and Recognition System for Assistive Driving
Road traffic accidents are primarily caused by drivers error. Safer roads infrastructure and facilities like traffic signs and signals are built to aid drivers on the road. But several factors affect the awareness of drivers to traffic signs including visual complexity, environmental condition, and poor drivers education. This led to the development of different ADAs…
Read MoreObject Classifications by Image Super-Resolution Preprocessing for Convolutional Neural Networks
Blurred small objects produced by cropping, warping, or intrinsically so, are challenging to detect and classify. Therefore, much recent research is focused on feature extraction built on Faster R-CNN and follow-up systems. In particular, RPN, SPP, FPN, SSD, and DSSD are the layered feature extraction methods for multiple object detections and small objects. However, super-resolution…
Read MoreAn Alternative Approach for Thai Automatic Speech Recognition Based on the CNN-based Keyword Spotting with Real-World Application
An automatic speech recognition (ASR) is a key technology for preventing an ongoing global coronavirus epidemic. Due to the limited corpus database and the morphological diversity of the Thai language, Thai speech recognition is still difficult. In this research, the automatic speech recognition model was built differently from the traditional Thai NLP systems by using…
Read MoreAdvanced Multiple Linear Regression Based Dark Channel Prior Applied on Dehazing Image and Generating Synthetic Haze
Haze removal is an extremely challenging task, and object detection in the hazy environment has recently gained much attention due to the popularity of autonomous driving and traffic surveillance. In this work, the authors propose a multiple linear regression haze removal model based on a widely adopted dehazing algorithm named Dark Channel Prior. Training this…
Read MoreDeep Learning Model for A Driver Assistance System to Increase Visibility on A Foggy Road
For many years, a lot of researches have been made to develop Advanced Driver Assistance Systems (ADAS) that are based on integrated systems. The main objective is to help drivers. Hence, keeping them safe under different driving conditions. Visibility for drivers remains the biggest problem faced on the road in an atmosphere of fog. In…
Read MoreCNN-based Automatic Coating Inspection System
The application of protective coatings is the primary method of protecting marine and offshore structures from corrosion. Coating breakdown and corrosion (CBC) assessment is a major aspect of coating failure management. Evaluation methods can result in unnecessary maintenance costs and a higher risk of failure. To achieve a comprehensive collection of data for CBC assessment,…
Read MoreReal Time Advanced Clustering System
This paper describes a system to gather information from a stationary camera to identify moving objects. The proposed solution makes only use of motion vectors between adjacent frames, obtained from any algorithm. Starting from them, the system is able to retrieve clusters of moving objects in a scene acquired by an image sensor device. Since…
Read MorePrototype Design Internet of Things Based Waste Management Using Image Processing
Waste is currently a serious problem often found in rural areas, rural areas, and even industrial areas. Waste is a side effect of activities carried out by humans to meet social or industrial needs. Increasing human productivity will also increase the amount of waste produced. To overcome this, a sorting management system is needed. Good…
Read More
