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Providing timely and meaningful feedback in photography education is challenging, particularly in large classes where manual assessment can delay skill development. This paper presents M-Stock, an AI-based automated photo evaluation system that uses Convolutional Neural Networks (CNNs) to assess student photography assignments on web browser. M-Stock evaluates both technical aspects (such as lighting, composition, and…

Being known as an irreversible neurodegenerative disease which has no cure to date, detection and classification of Alzheimer’s disease (AD) in its early stages is significant so that the deterioration process can be slowed down. Generally, AD can be classified into three major stages, ranging from the “normal control” stage with no symptoms shown, the…

The deep learning-based URL classification approach using massive observations has been verified especially in the field of phishing attack detection. Various improvements have been achieved through the modeling of character and word sequence of URL based on convolutional and recurrent neural networks, and it has been proven that an ensemble approach of each model has…

Face Recognition (FR) is considered as a heavily studied topic in computer vision field. The capability to automatically identify and authenticate human’s faces using real-time images is an important aspect in surveillance, security, and other related domains. There are separate applications that help in identifying individuals at specific locations which help in detecting intruders. The…

Programming industrial robots in a real-life environment is a significant task necessary to be dealt with in modern facilities. The “pick up and place” task is undeniably one of the regular robot programming problems which needs to be solved. At the beginning of the “pick and place” task, the position determination and exact detection of…

The use of Unmanned Aerial Vehicle (UAV) can contribute to find solutions and add value to several agricultural problems, favoring thus productivity, better quality control processes and flexible farm management. In addition, the strategies that allow the acquisition and analysis of data from agricultural environments can help optimize current practices such as crop counting. The…

Depth prediction plays a key role in understanding a 3D scene. Several techniques have been developed throughout the years, among which Convolutional Neural Network has recently achieved state-of-the-art performance on estimating depth from a single image. However, traditional CNNs suffer from the lower resolution and information loss caused by the pooling layers. And oversized parameters…

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…

Gender detection and age estimation become an active research area and a very important field today, wish has been widely used in various applications including them: biometrics, social network, Targeted advertising, access control, human-computer interaction, electronic customer, etc. The need to further improve the recognition or classification rate keeps increasing day after day. In this…

The large and ever-increasing variety of remote sensing sensors used in satellite imagery today explains why detecting changes between identical locations in images that are captured, at two separate times, from heterogeneous capturing systems is a major and challenging recent research problem in the field of satellite imaging for fast and accurate determination of temporal…

Analysis and classification of lung diseases using X-ray images is a primary step in the procedure of pneumonia diagnosis, especially in a critical period as pandemic of COVID-19 that is type of pneumonia. Therefore, an automatic method with high accuracy of classification is needed to perform classification of lung diseases due to the increasing number…

Suppose we want to classify a query item Q with a classification model that consists of a large set of predefined classes L and suppose we have a knowledge that indicates to us that the target class of Q belongs to a small subset from L. Naturally, this filtering will improve the accuracy of any…

Vietnam is one of the top 5 largest shrimp exporters globally, and Mekong delta of Vietnam contributes more than 80% of total national production. Along with intensive farming and growing shrimp farming area, diseases are a severe threat to productivity and sustainable development. Timely response to emerging shrimp diseases is critical. Early detection and treatment…

Restoring, estimating the fully 3D hand skeleton and pose from the image data of the captured sensors/cameras applied in many applications of computer vision and robotics: human-computer interaction; gesture recognition, interactive games, Computer-Aided Design (CAD), sign languages, action recognition, etc. These are applications that flourish in Virtual Reality and Augmented Reality (VR/AR) technologies. Previous survey…

This paper presents a solution that automates Abaca fiber grading which would help the time-consuming baling of Abaca fiber produce. The study introduces an objective instrument paired with a system to automate the grade classification of Abaca fiber using Convolutional Neural Network (CNN). In this study, 140 sample images of abaca fibers were used, which…

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…

In order to further improve the feature extraction performance of the convolutional neural networks, we focus on the selection and reorganization of key features and suspect that simple changes in the pooling layers can cause changes in the performance of neural networks. According to the conjecture, we design a funnel convolution module, which can filter…

TransJakarta is one of the methods to reduce congestion in Jakarta. However, the number of TransJakarta users compared to number of private vehicle users is very small, only 24% of the total population in Jakarta. The purpose of this research is to know public opinions about TransJakarta whether positive or negative by doing sentiment analysis…

We present findings on classifying the class of executable code using convolutional, re- current neural networks by creating images from only the .text section of executables and dividing them into standard-size windows, using minimal preprocessing. We achieve up to 98.24% testing accuracy on classifying 9 types of malware, and 99.50% testing accuracy on classifying malicious…

Convolutional LSTMs are widely used for spatiotemporal prediction. We study the effect of using different activation functions for two types of units within convolutional LSTM modules, namely gate units and non-gate units. The research provides guidance for choosing the best activation function to use in convolutional LSTMs for video prediction. Moreover, this paper studies the…

Low contrast images degrade the performance of image processing system. To solve the issue, plenty of image enhancement methods have been proposed. But the methods work properly on the fixed environment or specific images. The methods dependent on fixed image conditions cannot perform image enhancement properly and perspective of smart device users, algorithms including iterative…

Convolutional Neural Networks (CNNs) have gained attention in recent years for their ability to perform complex machine learning tasks with high accuracy and resilient to noise of inputs. The time-consuming convolution operations of CNNs pose great challenges to both software as well as hardware designers. To achieve superior performance, a design involves careful concerns between…

Neural Networks derives intelligent systems and modern autonomous applications. With the complexity introduced in today’s systems, designing architectures remains open research problem in all fields. Despite many efforts to generalize, the resources required by neural architectures remain challenge. Robots design, Smart cities, IoTs …etc. become the leading industry and driving the fourth industrial revolutions. All…

Skin cancer stands among some of the fastest growing and fatal malignancies of the world as a result early and accurate diagnosis of skin cancer is essential in order to enhance patient survival and treatment prognosis. Conventional methods of diagnosis including dermoscopy and histopathological examinations are expensive and time consuming also subject to inter-observer error.…

As models based in artificial intelligence increase in sophistication, there is a higher demand for the integration of hardware components to heighten real-world implementations. Both facial feature tracking and shape-from-focus are known techniques in computer vision. However, the combination of these two elements, particularly in a cost-effective configuration, has not been extensively explored. In this…