Shahzad Ahmed 교수

Human–Computer Interfaces (HCI) deals with the study of interface between humans and computers. The use of radar and other RF sensors to develop HCI based on Hand Gesture Recognition (HGR) has gained increasing attention over the past decade. Today, devices have built-in radars for recognizing and categorizing hand movements. In this article, we present the first ever review related to HGR using radar sensors. We review the available techniques for multi-domain hand gestures data representation

The emerging integration of technology in daily lives has increased the need for more convenient methods for human-computer interaction (HCI). Given that the existing HCI approaches exhibit various limitations, hand gesture recognition-based HCI may serve as a more natural mode of man-machine interaction in many situations. Inspired by an inception module-based deep-learning network (GoogLeNet), this paper presents a novel hand gesture recognition technique for impulse-radio ultra-wideband (IR-U

Hand gestures, being a convenient and natural way of communication, is getting huge attention for human–computer interface designs. Among these gestures, detecting mid-air writing is one of the most promising applications. Existing radar-based solutions often perform the mid-air writing recognition by tracking the hand trajectory using multiple monostatic or bistatic radars. This article presents a multistream convolutional neural network (MS-CNN)-based in-air digits recognition method using a f

In the past few decades, deep learning algorithms have become more prevalent for signal detection and classification. To design machine learning algorithms, however, an adequate dataset is required. Motivated by the existence of several open-source camera-based hand gesture datasets, this descriptor presents UWB-Gestures, the first public dataset of twelve dynamic hand gestures acquired with ultra-wideband (UWB) impulse radars. The dataset contains a total of 9,600 samples gathered from eight di

The unprecedented non-contact, non-invasive, and privacy-preserving nature of radar sensors has enabled various healthcare applications, including vital sign monitoring, fall detection, gait analysis, activity recognition, fitness evaluation, and sleep monitoring. Machine learning (ML) is revolutionizing every domain, with radar-based healthcare being no exception. Progress in the field of healthcare radars and ML is complementing the existing radar-based healthcare industry. This article provid

The diversion of a driver's attention from driving can be catastrophic. Given that conventional button- and touch-based interfaces may distract the driver, developing novel distraction-free interfaces for the various devices present in cars has becomes necessary. Hand gesture recognition may provide an alternative interface inside cars. Given that cars are the targeted application area, we determined the optimal location for the radar sensor, so that the signal reflected from the driver's hand d

Human Activity Recognition (HAR) has found many applications in several disciplines such as smart home and elderly healthcare units. The robustness of radar sensor against the environmental conditions make it a suitable candidate to recognize human activities. In this paper, we used Frequency Modulated Continuous Wave Radar (FMCW) radar for recog-nizing human activities in an unconstrained environment. Seven different activities are performed randomly at different distances from radar and a mult

Uterine leiomyosarcoma (ULMS) is the most common sarcoma of the uterus, It is aggressive and has poor prognosis. Its diagnosis is sometimes challenging owing to its resemblance by benign smooth muscle neoplasms of the uterus. Pathologists diagnose and grade leiomyosarcoma based on three standard criteria (i.e., mitosis count, necrosis, and nuclear atypia). Among these, mitosis count is the most important and challenging biomarker. In general, pathologists use the traditional manual counting meth

Remote sensing technology has been modernized by artificial intelligence, which has made it possible for deep learning algorithms to extract useful information from images. However, overfitting and lack of uncertainty quantification, high-resolution images, information loss in traditional feature extraction, and background information retrieval for detected objects limit the use of deep learning models in various remote sensing applications. This paper proposes a Bayes by backpropagation (BBB)-b

Short-range millimeter wave radar sensors provide a reliable, continuous and non-contact solution for vital sign extraction. Off-The-Shelf (OTS) radars often have a directional antenna (beam) pattern. The transmitted wave has a conical main lobe, and power of the received target echoes deteriorate as we move away from the center point of the lobe. While measuring vital signs, the human subject is often located at the center of the antenna lobe. Since beamforming can increase signal quality at th

Point clouds (PCs) are ubiquitous data representation schemas in complex tasks related to semantic segmentation and scene understanding. Contrary to vision-based approaches, radars, being a privacy-preserving sensor, are lately getting huge attention in generating PCs for medical applications since such sensors can be embedded into hospitals and living spaces. This article summarizes the use of radar-generated PCs in the healthcare and assisted living domain. Comparative analysis of radar and ot

Spontaneous abortion, commonly known as miscarriage, is a significant concern during early pregnancy. Histopathological examination of tissue samples is a widely used method to diagnose and classify tissue phenotypes found in products of conception (POC) after spontaneous abortion. <b>Background:</b> Histopathological examination is subjective and dependent on the skill and experience of the examiner. In recent years, artificial intelligence (AI)-based techniques have emerged as a promising tool

In this paper, we establish the empirical linkages between nominal and real variables of Pakistani economy using both annual and quarterly data. The focus of our empirical analysis has been limited to the post financial liberalization period starting in early 1990s. Furthermore, this paper theoretically evaluates the role of money and monetary policy in propagating business cycle fluctuations of Pakistani economy using different ways of introducing the role of money via money in utility (MIU) an

In this paper we will discuss about green manufacturing and its socio-economic aspects in steel and iron industry in current scenario of India. Challenges and opportunities will be discussed by taking example of a Chinese steel industry named Jinan Steel and Iron Group Corporation. Quantitative analysis was used to illustrate the effect of green manufacturing. Results show that measures of green manufacturing taken by in iron industry are effective and it is feasible and necessary to practice gr

Recently, radar sensors have been extensively used for vital sign monitoring in dogs, owing to their noncontact and noninvasive nature. However, a public dataset on dog vital signs has yet to be proposed since capturing data from dogs requires special training and approval. This work presents the first ever ultra wideband radar-based dog vital sign (UWB-DVS) dataset, which was captured in two independent scenarios. In the first scenario, clinical reference sensors are attached to the fainted dog