This data package(.zip) includes data of follower robots'  motion track、errors  and velocities in five simulatd experimental cases:(1),(2): set obstacle range on 0.8m and 1.0m,2 groups;(3):  oneside situation,  and the number of follower robots rises to 5.   (4):complex environment, which we place more obstacles.   (5): change the lead-follower formation  (6),(7):two types of formation tracks, circle and straight line,compare follower1,2.


Biometric management and that to which uses face, is indeed a very challenging work and requires a dedicated dataset which imbibes in it variations in pose, emotion and even occlusions. The Current work aims at delivering a dataset for training and testing purposes.SJB Face dataset is one such Indian face image dataset, which can be used to recognize faces. SJB Face dataset contains face images which were collected from digital camera. The face dataset collected has certain conditions such as different pose, Expressions, face partially occluded and with a uniform attire.


Retail Gaze, a dataset for remote gaze estimation in real-world retail environments. Retail Gaze is composed of 3,922 images of individuals looking at products in a retail environment, with 12 camera capture angles.

Each image captures the third-person view of the customer and shelves. Location of the gaze point, the Bounding box of the person's head, segmentation masks of the gazed at product areas are provided as annotations.


Holoscopic micro-gesture recognition (HoMG) database was recorded using a holoscopic 3D camera, which have 3 conventional gestures from 40 participants under different settings and conditions. The principle of holoscopic 3D (H3D) imaging mimics fly’s eye technique that captures a true 3D optical model of the scene using a microlens array. For the purpose of H3D micro-gesture recognition. HoMG database has two subsets. The video subset has 960 videos and the image subset has 30635 images, while both have three type of microgestures (classes).


The data set has been consolidated for the task of Human Posture Recognition. The data set consists of four postures namely -

  1. Sitting,
  2. Standing,
  3. Bending and,
  4. Lying.

There are 1200 images for each of the postures listed above. The images have a dimension of 512 x 512 px.


This article describes the possible design of the electron-ion trap combined density sensor and the composition of the upper atmosphere and simulation of the processes occurring in it. The simulation of the electric field between the electrodes of the trap and the motion of charged particles in it is carried out. The calculation of the maximum speed and energy of the particles below which the trap holds all charged particles, even in the case of the most unfavorable direction of their speed – along the gap between the electrodes.


Iris recognition has been an interesting subject for many research studies in the last two decades and has raised many challenges for the researchers. One new and interesting challenge in the iris studies is gender recognition using iris images. Gender classification can be applied to reduce processing time of the identification process. On the other hand, it can be used in applications such as access control systems, and gender-based marketing and so on. To the best of our knowledge, only a few numbers of studies are conducted on gender recognition through analysis of iris images.


This Dataset consist of 3Dmodels in Spherical harmonic coefficients andcorresponding shortcut of front view, the SH degree is 80.


Monitoring cell viability and proliferation in real-time provides a more comprehensive picture of the changes cells undergo during their lifecycle than can be achieved using traditional end-point assays. Our lab has developed a CMOS biosensor that monitors cell viability through high-resolution capacitance measurements of cell adhesion quality. The system consists of a 3 × 3 mm2 chip with an array of 16 sensors, on-chip digitization, and serial data output that can be interfaced with inexpensive off-the-shelf components.