Speech emotion recognition (SER) is the process of predicting human emotions from audio signals using artificial intelligence (AI) techniques. SER technologies have a wide range applications in areas such as psychology, medicine, education, and entertainment. Extracting relevant features crucial task to correctly identify emotions. Several studies on employed short-time Mel frequency cepstral coefficients (MFCCs), due their efficiency capturing periodic nature signals. However, these are...

Speaker identification refers to the process of recognizing human voice using artificial intelligence techniques. technologies are widely applied in authentication, security and surveillance, electronic eavesdropping, identity verification. In speaker process, extracting discriminative salient features from utterances is an important task accurately identify speakers. Various for have been recently proposed by researchers. Most studies on utilized short-time features, such as perceptual...

In recent years data science has been applied in a variety of real-life applications such as human-computer interaction applications, computer gaming, mobile services, and emotion evaluation. Among the wide range speech recognition (SER) is also an emerging challenging research topic. For SER, studies used handcrafted features that provide best results but failed to accuracy while complex scenarios. Later, deep learning techniques were for SER automatically detect from signals. Deep...

This study proposed an AlexNet-based crowd anomaly detection model in the video (image frames). The was comprised of four convolution layers (CLs) and three Fully Connected (FC). Rectified Linear Unit (ReLU) used as activation function, weights were adjusted through backpropagation process. first two CLs are followed by max-pool layer batch normalization. produced features that utilized to detect image frame. evaluated using parameters—Area Under Curve (AUC) Receiver Operator Characteristic...

With the continuous advancements in artificial intelligence, human activity recognition (HAR) technologies have garnered widespread attention and found applications across diverse domains. Recently, various features deep learning models are proposed for using sensors data. Though existing achieved notable performance, their accuracy needs to be enhanced computational cost reduced. This research introduces a novel integration of capsule network capable real-time signal processing. To...

Automatic Speaker Identification (ASI) involves the process of distinguishing an audio stream associated with numerous speakers’ utterances. Some common aspects, such as framework difference, overlapping different sound events, and presence various sources during recording, make ASI task much more complicated complex. This research proposes a deep learning model to improve accuracy system reduce training time under limited computation resources. In this research, performance transformer is...

Human activity recognition is a challenging and active research topic in computer science due to its applications video surveillance, health monitoring, rehabilitation, human-robot interaction, robotics, gesture posture analysis, sports. In the past, various studies have utilized manual features identify human activities obtained good accuracy. Nonetheless, performance of such degraded complex situations. Therefore, recent used deep learning (DL) techniques capture local automatically from...

Evapotranspiration (ET) is the fundamental component of efficient water resource management. Accurate forecasting ET essential for utilization in agriculture. a complex process due to requirements large meteorological variables. The recommended approach based on Internet Things (IoT) and an ensemble-learning-based data collection with limited conditions. IoT part collect real-time daily maximum temperature (T), mean humidity (Hm), wind speed (Ws) are used forecast evapotranspiration (ET)....

Accurate Evapotranspiration for saline soils (ETs) is important as well challenging the reclamation of through an effective leaching process. (ET) by FAO-56 Penman-Monteith standard method complex, especially soils. Moreover, existing studies focus on use Internet Things (IoT) and machine learning-enabled smart precision irrigation water recommendation systems along with ET estimation limited parameters. The ETs are also equally soils, which ignored literature. study proposed IoT...

Brain tumour disease develops due to abnormal cell proliferation. The early identification of brain tumours is vital for their effective treatment. Most currently available examination methods are laborious, require extensive manual instructions, and produce subpar findings. EfficientNet-B0 architecture was used diagnose using magnetic resonance imaging (MRI). fine-tuned EffeceintNet B0 model proposed the Internet Medical Things (IoMT) environment. employed classify four different stages...

Speaker Identification systems have become area of intense research in recent years due to its wide range applications voice matching, biometric identification, mobile access security, health care management and transportation. The major challenge speaker identification is how provide robust computationally efficient features that accurately captures speaker's unique identity for higher generalized identification. This paper presents hierarchical classification approach using time domain...

Environmental sound classification (ESC) involves the process of distinguishing an audio stream associated with numerous environmental sounds. Some common aspects such as framework difference, overlapping different events, and presence various sources during recording make ESC task much more complicated complex. This research is to propose a deep learning model improve recognition rate sounds reduce training time under limited computation resources. In this research, performance transformer...

The Coronavirus Disease 2019 (COVID-19) pandemic poses the worldwide challenges surpassing boundaries of country, religion, race, and economy. current benchmark method for detection COVID-19 is reverse transcription polymerase chain reaction (RT-PCR) testing. Nevertheless, this testing accurate enough diagnosis COVID-19. However, it time-consuming, expensive, expert-dependent, violates social distancing. In paper, research proposed an effective multi-modality-based feature fusion-based...

The proliferation of big data for web-enabled technologies allows users to publish their views, suggestions, sentiments, emotions, and opinionative content about several real-world entities. These available texts have greater importance those who are inquisitive desired entities, but it becomes an arduous task capture such a massive volume user-generated content. Emotions inseparable part communication, which is articulated in multiple ways can be used making better decisions reshape...