Abstract: An image processing method implemented by a processor includes receiving an image, acquiring a target image that includes an object from the image, calculating an evaluation score by evaluating a quality of the target image, and detecting the object from the target image based on the evaluation score.

Abstract: Implementations disclosed describe a system and a method to execute a virtual machine on a processing device, receive a request to access a memory page identified by a guest virtual memory address (GVA) in an address space of the virtual machine, translate the GVA to a guest physical memory address (GPA) using a guest page table (GPT) comprising a GPT entry mapping the GVA to the GPA, translate the GPA to a host physical address (HPA) of the memory page, store, in a translation lookaside buffer (TLB), a TLB entry mapping the GVA to the HPA, modify the GPT entry to designate the memory page as accessed, detect an attempt by an application to modify the GPT entry; generate, in response to the attempt to modify the GPT entry, a page fault; and flush, in response to the page fault, the TLB entry.

Abstract: Provided are a model generation method and apparatus, an object detection method and apparatus, a device and a storage medium. The method includes acquiring multiple scaling coefficients of a batch normalization layer in an initially-trained intermediate detection model, where the intermediate detection model is obtained by training an original detection model based on multiple training samples, and each training sample includes a sample image and a sample annotation result of a known object in the sample image; screening a to-be-pruned coefficient from the multiple scaling coefficients according to values of the multiple scaling coefficients; and screening a to-be-pruned channel corresponding to the to-be-pruned coefficient from multiple channels of the intermediate detection model and performing channel pruning on the to-be-pruned channel to generate an object detection model.

Abstract: Examples described herein relate to a packet processing device that includes circuitry to receive an address translation for a virtual to physical address prior to receipt of a GPUDirect remote direct memory access (RDMA) operation, wherein the address translation is provided at initiation of a process executed by a host system and circuitry to apply the address translation for a received GPUDirect RDMA operation.

Abstract: Glycosylated antitumor ether lipids (GAELs) are effective cytotoxic agents against cancer stem cells. Furthermore, combining GAELs which kill cells by a caspase-independent pathway with agents that kill cells by apoptosis will lead to elimination of the differentiated tumor cells and the undifferentiated cancer stem cells leading to an elimination of the tumor and preventing recurrence.

Abstract: Disclosed is a liveness test method and apparatus. A liveness test apparatus determines a pre-liveness score based on a plurality of sub-images acquired from an input image, determines a post-liveness score based on a recognition model for recognizing an object included in the input image, and determines a liveness of the object based on any one or any combination of the pre-liveness score and the post-liveness score.

Abstract: Implementations disclosed describe a system and a method to execute a virtual machine on a processing device, receive a request to access a memory page identified by a guest virtual memory address (GVA) in an address space of the virtual machine, translate the GVA to a guest physical memory address (GPA) using a guest page table (GPT) comprising a GPT entry mapping the GVA to the GPA, translate the GPA to a host physical address (HPA) of the memory page, store, in a translation lookaside buffer (TLB), a TLB entry mapping the GVA to the HPA, modify the GPT entry to designate the memory page as accessed, detect an attempt by an application to modify the GPT entry; generate, in response to the attempt to modify the GPT entry, a page fault; and flush, in response to the page fault, the TLB entry.

Abstract: An image processing method implemented by a processor includes receiving an image, acquiring a target image that includes an object from the image, calculating an evaluation score by evaluating a quality of the target image, and detecting the object from the target image based on the evaluation score.

Abstract: Implementations disclosed describe a system and a method to execute a virtual machine on a processing device, receive a request to access a memory page identified by a guest virtual memory address (GVA) in an address space of the virtual machine, translate the GVA to a guest physical memory address (GPA) using a guest page table (GPT) comprising a GPT entry mapping the GVA to the GPA, translate the GPA to a host physical address (HPA) of the memory page, store, in a translation lookaside buffer (TLB), a TLB entry mapping the GVA to the HPA, modify the GPT entry to designate the memory page as accessed, detect an attempt by an application to modify the GPT entry; generate, in response to the attempt to modify the GPT entry, a page fault; and flush, in response to the page fault, the TLB entry.

Abstract: Methods, software, and apparatus for application transparent, high available GPU computing with VM checkpointing. The guest access of certain GPU resources, such as MMIO resources, are trapped to keep a copy of guest context per semantics, and/or emulate the guest access of the resources prior to submission to the GPU, while other commands relating to certain graphics memory address regions are trapped before being passed through to the GPU. The trapped commands are scanned before submission to predict: a) potential to-be-dirtied graphics memory pages, and b) the execution time of intercepted commands, so the next checkpointing can be aligned to a predicted execution time. The GPU internal states are drained by flushing internal context/tlb/cache, at the completion of submitted commands, and then a snapshot of the vGPU state is taken, based on tracked GPU state, GPU context (through GPU-specific commands), detected dirty graphics memory pages and predicted to-be dirtied graphics memory pages.

Abstract: An image processing method implemented by a processor includes receiving an image, acquiring a target image that includes an object from the image, calculating an evaluation score by evaluating a quality of the target image, and detecting the object from the target image based on the evaluation score.

Abstract: An image processing apparatus, includes an image classifier configured to determine whether an input image is a low-quality image or a high-quality image; and an image evaluator configured to determine a first predetermined number of clearest images from a plurality of low-quality images determined by the image classifier.

Abstract: A processor implemented image processing method includes acquiring a facial image by performing a face detection on an image, performing a quality assessment on the facial image using a preset facial image regression model, and determining a quality level of the facial image based on the quality assessment.

Abstract: Disclosed is a liveness test method and apparatus. A liveness test apparatus determines a pre-liveness score based on a plurality of sub-images acquired from an input image, determines a post-liveness score based on a recognition model for recognizing an object included in the input image, and determines a liveness of the object based on any one or any combination of the pre-liveness score and the post-liveness score.

Abstract: A method of detecting a target includes determining a quality type of a target image captured using a camera, determining a convolutional neural network of a quality type corresponding to the quality type of the target image in a database comprising convolutional neural networks, determining a detection value of the target image based on the convolutional neural network of the corresponding quality type, and determining whether a target in the target image is a true target based on the detection value of the target image.

Abstract: Disclosed is a liveness test method and apparatus. A liveness test apparatus determines a pre-liveness score based on a plurality of sub-images acquired from an input image, determines a post-liveness score based on a recognition model for recognizing an object included in the input image, and determines a liveness of the object based on any one or any combination of the pre-liveness score and the post-liveness score.

Abstract: The present disclosure provides a virtualization method for a device MMU, including: multiplexing a client MMU as a first layer address translation: a client device page table translates a device virtual address into a client physical address; using IOMMU to construct a second layer address translation: IOMMU translates the client physical address into a host physical address through a TO page table of a corresponding device in IOMMU. The virtualization method for a device MMU proposed by the present disclosure can efficiently virtualize the device MMU; successfully combines IOMMU into Mediated Pass-Through, and uses the system IOMMU to perform the second layer address translation, such that the complicated and inefficient Shadow Page Table is abandoned; not only improves the performance of the device MMU under virtualization, but also is simple to implement and completely transparent to the client, and is a universal and efficient solution.

Abstract: Implementations disclosed describe a system and a method to execute a virtual machine on a processing device, receive a request to access a memory page identified by a guest virtual memory address (GVA) in an address space of the virtual machine, translate the GVA to a guest physical memory address (GPA) using a guest page table (GPT) comprising a GPT entry mapping the GVA to the GPA, translate the GPA to a host physical address (HPA) of the memory page, store, in a translation lookaside buffer (TLB), a TLB entry mapping the GVA to the HPA, modify the GPT entry to designate the memory page as accessed, detect an attempt by an application to modify the GPT entry; generate, in response to the attempt to modify the GPT entry, a page fault; and flush, in response to the page fault, the TLB entry.

Abstract: An apparatus, system, method, and machine-readable medium are disclosed. In one embodiment the apparatus is a network interface controller that includes one virtual function owned by a virtual machine present in the computer system. The controller includes a simple filtering agent that is associated with the first virtual function. The agent enforces simple filter rules for received network packets. The simple filter rules are capable of blocking the network packets from reaching the virtual machine. The apparatus also includes another virtual function that is owned by a virtual machine monitor present in the computer system. The controller also includes a side bounce filtering agent to forward the first network packet to the second virtual function if the first packet is blocked by the at least one of the one or more simple filter rules.

Abstract: Disclosed is a liveness test method and apparatus. A liveness test apparatus determines a pre-liveness score based on a plurality of sub-images acquired from an input image, determines a post-liveness score based on a recognition model for recognizing an object included in the input image, and determines a liveness of the object based on any one or any combination of the pre-liveness score and the post-liveness score.