The objective of this research work is to classify brain tumor images into 4 different classes by using Convolutional Neural Network (CNN) algorithm i.e. a deep learning method with VGG16 architecture. four are pituitary, glioma, meningioma, and no tumor. dataset used for publicly available MRI Image 7023 images. methodology followed in project includes data pre-processing, model building, eval...

Abstract: Facial expression recognition is a powerful tool for communicating our emotions, understanding, and intent with each other. It an intelligent human-computer interaction technology. Various studies have been conducted to classify facial expressions. Six fundamental universal emotions can be expressed through expressions: happiness, sadness, anger, fearful, surprised, neutral. In this p...

The Internet of Things (IoT) and artificial intelligence (AI) based methods for monitoring, control, decision support are combined to design a smart agriculture assistance system. proposed system has sensor pack that provides continuous data capture temperature records, air soil moisture camera obtaining near-infrared (NIR) images the plant leaves use with an AI We identify twelve types vegetat...

In recent years, convolutional neural network (CNN)-based algorithms have been widely used in remote sensing image processing and show tremendous performance a variety of application fields. However, large amounts data intensive computations make the deployment CNN-based challenging problem, especially for spaceborne scenario where resources power consumption are limited. To tackle this paper p...

Energy and throughput efficient acceleration of convolutional neural networks (CNN) on devices with a strict power budget is achieved by leveraging different scheduling techniques to minimize data movement maximize reuse. Several dataflow mapping frameworks have been developed explore the optimal CNN layers reconfigurable accelerators. However, previous works usually optimize each layer singula...

Automated methods intended for image classification have become increasingly popular in recent years, with applications the agriculture field including weed identification, fruit classification, and disease detection plants trees. In convolutional neural networks (CNN) already shown exceptional results but problem these models is that cannot extract some relevant features of input image. On oth...

In this paper, we study the dynamic range of multi-layer cellular neural networks (CNN’s) by using Lyapunov functions. A theorem is presented to guarantee the existence of equilibrium point of multi-layer CNN. A theorem on globally stable equilibrium point of multi-layer CNN is given. Multi-layer CNN’s are used to model some functions of nitric oxide (NO) in nervous systems. In a 2-layer CNN mo...

Pneumonia is the leading cause of death from a single infection worldwide in children. A proven clinical method for diagnosing pneumonia through chest X-ray. However, resulting X-ray images often need clarification, subjective judgments. In addition, process diagnosis requires longer time. One technique can be applied by applying advanced deep learning, namely, Transfer Learning with Deep Convo...

Vehicle classification is a challenging task in the area of image processing. It involves various vehicles based on their color, model, and make. A distinctive variety belonging to model categories have been developed automobile industry, which has made it necessary establish compact system that can classify within complex group. well-established vehicle applications security, monitoring traffi...

In this work, we present an approach to understand the computational methods and decision-making involved in identification of emotions spontaneous speech. The selected task consists Spanish TV debates, which entail a high level complexity as well additional subjectivity human perception-based annotation procedure. A simple convolutional neural model is proposed, its behaviour analysed explain ...